Literature DB >> 30893732

Regional and seasonal variations of outdoor thermal comfort in China from 1966 to 2016.

Feifei Wu1, Xiaohua Yang2, Zhenyao Shen1.   

Abstract

The optimized design of outdoor environment is of utmost importance due to its impact on human health, urban livability and energy consumption inside buildings. The outdoor thermal comfort and its spatiotemporal variations were assessed using Universal Thermal Climate Index (UTCI). Annual and seasonal UTCI were calculated using the daily dataset collected from 591 stations in China between 1966 and 2016. A REOF-cluster-EOF hybrid model was developed to optimize regionalization and assess regional-scale variations for UTCI. The results showed the following: (1) UTCI values decreased due to the increase of the latitude in China except for the Qinghai-Tibet Plateau. 69.5% of the total area of China experienced "no thermal stress" conditions in summer, whereas it was only 7.7% in winter. Additionally, the outdoor environment in summer had a wider "thermal comfort zone" than that in other seasons. (2) China was divided into a small number of regions with coherent UTCI changes using REOF analysis and K-means clustering algorithm. Eight homogeneous regions were obtained for annual UTCI. From spring to winter, the numbers of homogeneous regions were eight, nine, ten and seven, respectively. (3) Using EOF analysis, dominant patterns of UTCI in each region were extracted by the first two EOF modes, which accounted for >60% of the total variance. In the first mode, the significant upward trends of UTCI were detected in each region, suggesting the stronger outdoor heat stress. In the second mode, UTCI showed fluctuation between the cold and warm periods with different turning points between regions. Overall, the outdoor thermal comfort seemed to be improved more in high-latitude regions than that in low-latitude regions.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  China; Empirical orthogonal function (EOF) analysis; K-mean clustering algorithm; Outdoor thermal comfort; Regionalization; Universal Thermal Climate Index (UTCI)

Year:  2019        PMID: 30893732     DOI: 10.1016/j.scitotenv.2019.02.190

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


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